Gravitational Wave Noise Hunting
Gravitational Wave noise hunting will develop a cutting-edge citizen science programme by providing public access to GW antenna data, including environmental data, for an open-data project.
The sensitivity of GW detectors is limited by several types of noise and requires recognition on how they affect GW data is crucial to understand their origin and eliminate them. The result of this activity of noise hunting and profiling is crucial to be more sensitive to GW Signals, including those that are not modelled by general relativity formula, such as those from the explosion of supernovae.
Citizen scientists will contribute to this activity by looking at chunks of data and identify the presence of noise, and this outcome will serve as a basis to train machine learning algorithms that will automatically recognize and isolate noise in GW data. The same approach can also be used for seismic applications and/or earthquake. The team is already working in collaboration with the team of GravitySpy, a highly successful citizen science project base on recognition of transient noise sources called glitches. The experience of the LIGO Gravity-SPY programme will be central here. The University of Oxford has many Zooniverse resources and technologies than can be usefully deployed here. In the framework of the “Gravitational Wave noise hunting” demonstrator, the option is to develop multi-messenger techniques in citizens science will be investigated.
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